class_docstr: Squeeze and excitation block that acts as the attention module in SSPCAB.
  
  Args:
      channels (int): Number of input channels.
      reduction_ratio (int): Reduction ratio of the attention module.
code: def __init__(self, in_channels: int, reduction_ratio: int = 8):
      super().__init__()
  
      out_channels = in_channels // reduction_ratio
      self.fc1 = nn.Linear(in_channels, out_channels)
      self.fc2 = nn.Linear(out_channels, in_channels)
  
file_path: anomalib/src/anomalib/models/components/layers/sspcab.py
imports: import torch
  import torch.nn.functional
  from torch import Tensor, nn
label_desc: Use image node_id 1 to create a new AttentionModule object from inherited base classes: nn with example: obj = AttentionModule(in_channels, reduction_ratio)